Evidence map›Paper›PMID 39762471›Full record

ArticleScientific reports2025

A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer.

Prarthana Chatterjee, Satarupa Banerjee

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

  1. Article
  2. Cancer-associated TRF1 mutations alter PARP1 interaction dynamics: an in silico study.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
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5 · Who and what money

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2 authors.

Prarthana ChatterjeeSchool of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
Satarupa BanerjeeSchool of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India. satarupa.banerjee@vit.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The proliferation-specific oncogenic transcription factor, FOXM1 is overexpressed in primary and recurrent breast tumors across all breast cancer (BC) subtypes. Intriguingly, FOXM1 overexpression was found to be highest in Triple-negative breast cancer (TNBC), the most aggressive BC with the worst prognosis. However, FOXM1-mediated TNBC pathogenesis is not completely elucidated. Single nucleotide polymorphisms (SNPs) are the most common genetic variations causing functional and structural aberrations in proteins enhancing cancer susceptibility. This computational investigation attempted to identify the malignant FOXM1 non-synonymous SNPs (nsSNPs) and evaluate their role in affecting the conformational and functional stability, evolutionary conservation, post-translational modifications, and malignant susceptibility of the protein. Out of a huge data pool of 8826 FOXM1 SNPs using several in-silico sequence-based tools and structural approaches, four SNPs viz. E235Q, R256C, G429E and S756P were identified as pathogenic nsSNPs and among the shortlisted variants molecular dynamics simulations identified E235Q as the most damaging malignant SNP, followed by S756P. Additionally, the defective drug and DNA binding motif of E235Q and S756P were also determined in our study. Thus, although further in-vitro validations are awaited the findings of this in-silico work can be used as a blueprint for malignant nsSNP identification of FOXM1 aiding in clinical TNBC therapeutics.

Indexed as

Forkhead Box Protein M1Molecular Dynamics SimulationPolymorphism, Single NucleotideTriple Negative Breast NeoplasmsComputational BiologyFemaleGenetic Predisposition to DiseaseHumansForkhead Box Protein M1FOXM1 protein, humanFOXM1Molecular dynamic simulationsSingle nucleotide polymorphismsTriple-negative breast cancer

Identifiers

PMID39762471
PMCPMC11704209

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